11,176 research outputs found
Multi-mode resource constrained multi-project scheduling and resource portfolio problem
This paper introduces a multi-project problem environment which involves
multiple projects with assigned due dates; with activities that have alternative
resource usage modes; a resource dedication policy that does not allow
sharing of resources among projects throughout the planning horizon; and a
total budget. There are three issues to face when investigating this multiproject environment. First, the total budget should be distributed among
different resource types to determine the general resource capacities which
correspond to the total amount for each renewable resource to be dedicated
to the projects. With the general resource capacities at hand, the next issue
is to determine the amounts of resources to be dedicated to the individual
projects. With the dedication of resources accomplished, the scheduling
of the projects' activities reduces to the multi-mode resource constrained
project scheduling problem (MRCPSP) for each individual project. Finally
the last issue is the effcient solution of the resulting MRCPSPs. In this paper,
this multi-project environment is modeled in an integrated fashion and designated as the Resource Portfolio Problem. A two-phase and a monolithic
genetic algorithm are proposed as two solution approaches each of which
employs a new improvement move designated as the combinatorial auction
for resource portfolio and the combinatorial auction for resource dedication.
Computational study using test problems demonstrated the effectiveness of
the solution approach proposed
Multi-mode resource constrained multi-project scheduling and resource portfolio problem
This paper introduces a multi-project problem environment which involves
multiple projects with assigned due dates; activities that have alternative resource usage modes; a resource dedication policy that does not allow sharing
of resources among projects throughout the planning horizon; and a total
budget. Three issues arise when investigating this multi-project environment.
First, the total budget should be distributed among different resource
types to determine the general resource capacities, which correspond to the
total amount for each renewable resource to be dedicated to the projects.
With the general resource capacities at hand, the next issue is to determine
the amounts of resources to be dedicated to the individual projects. The
dedication of resources reduces the scheduling of the projects' activities to
a multi-mode resource constrained project scheduling problem (MRCPSP)for each individual project. Finally, the last issue is the ecient solution
of the resulting MRCPSPs. In this paper, this multi-project environment is
modeled in an integrated fashion and designated as the Resource Portfolio
Problem. A two-phase and a monolithic genetic algorithm are proposed as
two solution approaches, each of which employs a new improvement move
designated as the combinatorial auction for resource portfolio and the combinatorial auction for resource dedication. A computational study using test
problems demonstrated the effectiveness of the solution approach proposed.
Keywords: Project scheduling, resource portfolio problem, multi-project
scheduling, resource dedication, resource preference
Resource preference based improvement heuristics for resource portfolio problem
The multi-project problem environment under consideration involves multiple-projects with activities having alternative execution modes, a general resource budget and a resource management policy that does not allow sharing of resources among projects. The multi-project scheduling model for this problem environment is called Resource Portfolio Problem. There are three basic conceptual problems in RPP: (i) determining the general resource capacities from the given general resource budget (general resource capacities determination); (ii) dedication of the general resource capacities to projects (resource dedication) and finally (iii) scheduling of individual projects with the given resource dedications. In this study, different preference based improvement heuristics are proposed for general resource capacities determination and resource dedication conceptual problems. For general resource capacities determination, the current general resource capacity values are changed according to the resource preferences such that the resulting capacity state would be more preferable. Similarly for resource dedication, resource
dedication values of projects are changed according to the preferences of projects for resources such that the resulting resource dedication state would be more preferable. These two improvement heuristics separates and couples the conceptual problems. Different preference calculation methods are proposed employing Lagrangian relaxation and linear relaxation of MRCPSP formulation
A modied branch and cut procedure for resource portfolio problem under relaxed resource dedication policy
Multi-project scheduling problems are characterized by the way resources are
managed in the problem environment. The general approach in multi-project
scheduling literature is to consider resource capacities as a common pool that
can be shared among all projects without any restrictions or costs. The way
the resources are used in a multi-project environment is called resource management policy and the aforementioned assumption is called Resource Sharing
Policy in this study. The resource sharing policy is not a generalization
for multi-project scheduling environments and different resource management
policies maybe defined to identify characteristics of different problem environments.
In this study, we present a resource management policy which prevents sharing of resources among projects but allows resource transfers when a project starts after the completion of another one. This policy is called the Relaxed Resource Dedication (RRD) Policy in this study. The general resource capacities might or might not be decision variables. We will treat here the case where the general available amounts of resources are decision variables to be determined subject to a limited budget. We call this problem as the Resource Portfolio Problem (RPP). In this study, RPP is investigated under RRD policy and a modified Branch and Cut (B&C)procedure based on CPLEX is proposed. The B&C procedure of CPLEX is modified with different branching strategies, heuristic solution approaches and valid inequalities. The computational studies presented demonstrate the effectiveness of the proposed solution approaches
Different resource management policies in multi-mode resource constrained multi-project scheduling
This study investigates different resource management policies in resource constrained multi-project problem environments. The problem environment under investigation has alternative modes for activities, a set of renewable and nonrenewable resources used by activities and further considerations such as general resource budget. The characterization of the way resources are used by individual projects in the multiproject environment is called resource management policy in this study. The solution approaches in the literature for multi-project problems generally defines the resources as a pool that can be shared by all the projects which in fact creates a general assumption for the resource usage characteristics. This resource management policy is referred as resource sharing policy in this study. Resource sharing policy can be invalid in
some certain cases where sharing assumption is not feasible because of some characteristics of resources and/or projects which require different resource management policies for the multi-project environment. According to the characteristics of resources and projects, resource management policies such as
resource dedication, relaxed resource dedication and generalized resource management policies can be defined. In this paper, these resource management policies will be defined and their mathematical formulations will be presented and discussed
A combination of different resource management policies in a multi-project environment
Multi-project problem environments are defined according to the way resources are managed in the problem environment, which is called the resource management policy (RMP) in this study. Different resource management policies can be
defined according to the characteristics of the projects and/or resources in the problem environment. The most common RMP encountered in the multi-project scheduling literature is the resource sharing policy (RSP), where resources can be shared among projects without any costs or limitations. This policy can be seen as an extreme case since there is a strong assumption of unconstrained resource sharing. Another RMP can be defined as the other extreme such that resources cannot be shared among projects, which is called the resource dedication policy (RDP). The last RMP considered in this study is between these two policies where resources are dedicated but can be transferred among projects when a project finishes, the dedicated resources to this project can be transferred to another one starting after the finish of the corresponding project. This RPM is called the resource transfer policy (RTP). In this study we investigate a problem environment where all these three types of RPM are present. Additionally, the general resource capacities are taken as decision variables that are constrained by a given general budget. We call this multi-project environment as the Generalized Resource Portfolio Problem (GRPP). We have investigated this problem and proposed an iterative solution approach based on exact solution methods which determines the general resource capacities from the budget, resource dedications, resource sharing and resource transfer decisions and schedules the individual projects. Computational results
for over forty test problems are reported
Dynamic resource constrained multi-project scheduling problem with weighted earliness/tardiness costs
In this study, a conceptual framework is given for the dynamic multi-project scheduling problem with weighted earliness/tardiness costs (DRCMPSPWET) and a mathematical programming formulation of the problem is provided. In DRCMPSPWET, a project arrives on top of an existing project portfolio and a due date has to be quoted for the new project while minimizing the costs of schedule changes. The objective function consists of the weighted earliness tardiness costs of the activities of the existing projects in the current baseline schedule plus a term that increases linearly with the anticipated completion time of the new project. An iterated local search based approach is developed for large instances of this problem. In order to analyze the performance and behavior of the proposed method, a new multi-project data set is created by controlling the total number of activities, the due date tightness, the due date range, the number of resource types, and the completion time factor in an instance. A series of computational experiments are carried out to test the performance of the local search approach. Exact solutions are provided for the small instances. The results indicate that the local search heuristic performs well in terms of both solution quality and solution time
Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
Purpose: The issue resource over-allocating is a big concern for project engineers in the process
of scheduling project activities. Resource over-allocating drawback is frequently seen after
scheduling of a project in practice which causes a schedule to be useless. Modifying an
over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a
new and fast tracking method is proposed to schedule large scale projects which can help project
engineers to schedule the project rapidly and with more confidence.
Design/methodology/approach: In this article, a forward approach for maximizing net
present value (NPV) in multi-mode resource constrained project scheduling problem while
assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment
method is used and all resources are considered as pre-emptible. The proposed approach
maximizes NPV using unscheduled resources through resource calendar in forward mode. For
this purpose, a Genetic Algorithm is applied to solve.
Findings: The findings show that the proposed method is an effective way to maximize NPV in
MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast
and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The
results are then compared with branch and bound method and simulated annealing algorithm and
it is found the proposed genetic algorithm can provide results with better quality. Then algorithm
is then applied for scheduling a hospital in practice.
Originality/value: The method can be used alone or as a macro in Microsoft Office Project®
Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities
after scheduling a project. This can help project engineers to schedule project activities rapidly
with more accuracy in practice.Peer Reviewe
Solution and quality robust project scheduling: a methodological framework.
The vast majority of the research efforts in project scheduling over the past several years has concentrated on the development of exact and suboptimal procedures for the generation of a baseline schedule assuming complete information and a deterministic environment. During execution, however, projects may be the subject of considerable uncertainty, which may lead to numerous schedule disruptions. Predictive-reactive scheduling refers to the process where a baseline schedule is developed prior to the start of the project and updated if necessary during project execution. It is the objective of this paper to review possible procedures for the generation of proactive (robust) schedules, which are as well as possible protected against schedule disruptions, and for the deployment of reactive scheduling procedures that may be used to revise or re-optimize the baseline schedule when unexpected events occur. We also offer a methodological framework that should allow project management to identify the proper scheduling methodology for different project scheduling environments. Finally, we survey the basics of Critical Chain scheduling and indicate in which environments it is useful.Framework; Information; Management; Processes; Project management; Project scheduling; Project scheduling under uncertainty; Stability; Robust scheduling; Quality; Scheduling; Stability; Uncertainty;
Welcome to OR&S! Where students, academics and professionals come together
In this manuscript, an overview is given of the activities done at the Operations Research and Scheduling (OR&S) research group of the faculty of Economics and Business Administration of Ghent University. Unlike the book published by [1] that gives a summary of all academic and professional activities done in the field of Project Management in collaboration with the OR&S group, the focus of the current manuscript lies on academic publications and the integration of these published results in teaching activities. An overview is given of the publications from the very beginning till today, and some of the topics that have led to publications are discussed in somewhat more detail. Moreover, it is shown how the research results have been used in the classroom to actively involve students in our research activities
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